AN EFFICIENCY INDICATOR TOOL FOR MANAGING RESOURCE EXPENDITURE IN PUBLIC CENTRAL HOSPITALS

Abstract:

Citizens generally assume that government has unlimited resources, but public health care services are always limited and constrained. Public hospitals are generally in dire need of opportunities to allocate resources efficiently in light of limited financial resources whilst in the private sector, affordability guarantees access (Alaba and McIntyre, 2012). Efficient hospital management should include harmonised health care activities and provision, based on application of knowledge and managerial skills, including problem-solving to achieve outcomes using resources in the most economical, efficient and effective way (Usman et al, 2015). This research investigated cause and effect relationships between the hospital efficiency indicators and some dimensions and sub dimensions of hospital performance, mainly costs and volume of health care activities.
Vector-Auto regression (VAR) system of models were applied to efficiency-indicator data for the four public central hospitals in Gauteng provided from District Health Information System (DHIS) over 28 time points which are quarterly intervals over 7 years (from 1st quarter 2008/09 to 4th quarter 2014/15). The rate of increment per quarter for each efficiency indicator was determined to be R44.02 for Expenditure per Patient Day Equivalent (ExPDE); 0.17% for Caesarean Section rates (C-Section); 0.31% for Bed Utilisation Rate (BUR) and 0.07 days for Average Length Of Stay (ALOS). The above estimates are generated in a predictive modelling context with smaller standard errors in comparison to those generated by traditional or conventional approaches and are therefore more precise. Linear Mixed Modelling also showed that correlating expenditure to efficiency would require hospital specific interventions due to significant ‘hospital specific characteristics or random effect’ (intra-class correlation) for each efficiency indicator. It was inferred that, whereas there might be common fixed costs associated with the operation of central hospitals, the cost pressure of providing for services is affected differently at each central hospital.
Inferences of managers’ subjective responses on their understanding and utilisation of efficiency-indicator information showed that a manager with a medical background or within patient care is 1.14 times more likely to comprehend efficiency information compared to one with a business or management background. Interaction with efficiency data in current role is 1.10 times more likely for managers in patient care than those in administration / support. After controlling for hospital specific effects, changes are recommended for determination of targets for Caesarean section rates, as well as for the current set of efficiency indicators to be expanded. An Efficiency Indicator Management Tool (EIMT), where predictive modelling capability is a major output of the research study, is presented as a strategic implementational tool to promote evidence-based data decision-making in public hospitals. This research is significant in that it realised how efficiency indicators can be adopted to guide hospital expenditure in a cost-effective way.

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